CoolFace
Datasetpublic

electricsheepafrica/africa-mauritius-budget-data-2016-2017-ministry-of-ocean-economy-marine-res-b1498e9c

Budget Data 2016 2017 Ministry of Ocean Economy Marine Res | Africa (MDPA) 612 rows - 1 Africa country/area - 2015-2018 - 3 indicators - Engineered by Electric Sheep Africa TL;DR This dataset contains 612 rows from MDPA, covering Budget Data 2016 2017 Ministry of Ocean Economy Marine Res. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This Dataset Measures… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-budget-data-2016-2017-ministry-of-ocean-economy-marine-res-b1498e9c.

sourceHugging Facecc-by-sa-4.0updated 2mo agoView on Hugging Face
0likes16downloads
Dataset Card

Budget Data 2016 2017 Ministry of Ocean Economy Marine Res | Africa (MDPA)

612 rows - 1 Africa country/area - 2015-2018 - 3 indicators - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 612 rows from MDPA, covering Budget Data 2016 2017 Ministry of Ocean Economy Marine Res. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Economic datasets help analysts examine production, prices, public finance, trade flows, market conditions, and macroeconomic change.

This dataset covers Budget Data 2016 2017 Ministry of Ocean Economy Marine Res from MDPA. Use the source and schema sections below to confirm definitions, units, and collection methodology before sensitive analytical use.

How To Read This Dataset

  • —One row means: one indicator observation for one geography, time period, and optional source dimensions.
  • —Primary geography column: country_iso3.
  • —Best time column: year.
  • —Time coverage basis: year.
  • —Recommended join keys: country_iso3, year, indicator_id.

Coverage

DimensionValue
Rows612
Countries/areas1
First period2015
Last period2018
Indicators3
Columns24
Source formatCSV

Geographic Coverage

Top areas shown below, sorted by row count when available:

AreaRowsFirst yearLast yearName
MU61220152018Mauritius

Indicators, Variables, Or Resource Contents

  • —budget-data-2016-2017-ministry-of-ocean-economy-marine-resources-fisheri-a85ba64d - Budget Data 2016-2017 - Ministry of Ocean Economy, Marine Resources, Fisheries and Shipping (Ocean Economy and Shipping) - itemno(sourceunitsunspecified)
  • —budget-data-2016-2017-ministry-of-ocean-economy-marine-resources-fisheri-7deb9f86 - Budget Data 2016-2017 - Ministry of Ocean Economy, Marine Resources, Fisheries and Shipping (Ocean Economy and Shipping) - endfinancialyear(sourceunitsunspecified)
  • —budget-data-2016-2017-ministry-of-ocean-economy-marine-resources-fisheri-e92fecec - Budget Data 2016-2017 - Ministry of Ocean Economy, Marine Resources, Fisheries and Shipping (Ocean Economy and Shipping) - amount(sourceunitsunspecified)

Schema

ColumnTypeDescriptionExample
indicator_idstringStable source or Electric Sheep Africa indicator identifier.budget-data-2016-2017-ministry-of-ocean-economy-marine-resources-fish...
indicator_namestringHuman-readable indicator name.Budget Data 2016-2017 - Ministry of Ocean Economy, Marine Resources, ...
country_iso3stringISO3 country or area code.MU
country_namestringCountry or area name.Mauritius
yearint64Observation year.2015
valuedoubleNumeric observation value.21110.0
unitstringMeasurement unit, when supplied by the source.source_units_unspecified
dimension_headstringSource dimension retained during long-form normalization.Ocean Economy Marine
dimension_subheadstringSource dimension retained during long-form normalization.General
dimension_expenditurestringSource dimension retained during long-form normalization.Recurrent
dimension_categorystringSource dimension retained during long-form normalization.Compensation of Employees
dimension_subcategorystringSource dimension retained during long-form normalization.Personal Emoluments
dimension_financebudgettypestringSource dimension retained during long-form normalization.Provisional Actual
source_period_start_yearint64Start year inferred from source metadata.2016
source_period_end_yearint64End year inferred from source metadata.2017
source_period_labeldictionary<values=string, indices=int8, ordered=0>Source column from the original resource.2016-2017
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.MDPA
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.Budget Data 2016-2017 - Ministry of Ocean Economy, Marine Resources, ...
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.DATA-Budget-2016_2017-OceanEconomy_and_Shipping_0.csv
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.e377fe58-7c3d-4256-916a-0a34322061bb
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.e2190ba9-c7ac-42c9-ac68-a84af5776cdb
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://data.govmu.org/dataset/e377fe58-7c3d-4256-916a-0a34322061bb/r...
license_iddictionary<values=string, indices=int8, ordered=0>Source license identifier.CC-BY-SA-4.0
retrieved_atdictionary<values=string, indices=int8, ordered=0>UTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-08-08T16:26:20Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-budget-data-2016-2017-ministry-of-ocean-economy-marine-res-b1498e9c")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

python
print(df.info())
print(df.head())

Filter By Geography

python
if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "MU"]

Time-Series Pattern

python
if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis

python
if {"indicator_id", "year", "value"}.issubset(df.columns):
    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
    print(matrix.tail())

Data Quality Notes

  • —Canonical time field: year.
  • —Missing values are preserved rather than silently imputed.
  • —Column names are standardized for machine use; source meanings are preserved where known.
  • —Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.

Source And Provenance

Transformations Applied

  • —Converted the source table to Parquet for efficient analytics and ML workflows.
  • —Added or preserved source provenance columns where available.
  • —Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
  • —Preserved source-reported values without analytical imputation.

Suggested Analyses

  • —Build time-series dashboards
  • —Compare economic indicators
  • —Join with population or sector data
  • —Build time-series views and period-over-period comparisons
  • —Pivot to geography x period or indicator x period matrices
  • —Check missingness before modeling
  • —Use country_iso3 as the safest geography join key when present

Citation

bibtex
@misc{electric_sheep_africa_africa_mauritius_budget_data_2016_2017_ministry_of_ocean_economy_marine_res_b149_2018,
  title        = {Budget Data 2016 2017 Ministry of Ocean Economy Marine Res | Africa (MDPA)},
  author       = {MDPA},
  year         = {2018},
  url          = {https://data.govmu.org/dataset/budget-data-2016-2017-ministry-ocean-economy-marine-resources-fisheries-and-shipping-ocean},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-budget-data-2016-2017-ministry-of-ocean-economy-marine-res-b1498e9c}}
}

License

Released under CC BY-SA 4.0.

Original data is published by MDPA. Electric Sheep Africa engineering standardizes the data for discovery, loading, and analysis on Hugging Face. Cite both the original source and this ML-ready dataset when used.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.


Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/budget-data-2016-2017-ministry-ocean-economy-marine-resources-fisheries-and-shipping-ocean